Updated 'Data Instances' and 'Data Fields' sections to include added test files

README.md

@@ -205,13 +205,20 @@ Each record in `train.csv` or `val.csv` corresponds to a single pinned carabid b
 
 Metadata include an identifier for a collection event (`eventID`), the date of the collection event (`collectDate`), an anonymized identifier of the domain (`domainID`) and site (`siteID`) where the collection event took place, taxonomic information (`scientificName`), unique beetle image identifier (`public_id`), a link to the beetle image file (`relative_img_loc`), a link to the color palette image (`colorpicker_path`), a link to the scale image (`scalebar_path`), and Standardized Precipication Evapotranspiratoin Index (SPEI) values that correspond with the location and time that the specimen was collected. The SPEI values were calculated for the 30 day (`SPEI_30d`), 1 year (`SPEI_1y`), and 2 year (`SPEI_2y`) time windows preceding the time of collection at each location for each beetle specimen in the dataset. 
 
-The `train.csv` and `val.csv` files are to be used for training models for submission and reflect the information that will be given during testing sans `siteID`, `collectDate`, and the target variables `SPEI_30d`, `SPEI_1y`, and `SPEI_2y`. Please see the [challenge sample repository](https://github.com/Imageomics/HDR-SMood-Challenge-sample) for an example of how these were used in training the baseline submission.
+The `train.csv` and `val.csv` files are to be used for training models for submission and reflect the information that will be given during testing sans `siteID`, `collectDate`, and the target variables `SPEI_30d`, `SPEI_1y`, and `SPEI_2y`. Please see the [challenge sample repository](https://github.com/Imageomics/HDR-SMood-Challenge-sample) for an example of how these were used in training the baseline submission. After the challenge the testings files `seen_domain.csv`, `seen_domain_challenge.csv`, `unseen_domain.csv`, `unseen_domain_challenge.csv` will be included with the same columns as `train.csv` and `val.csv`.
 
-The `data/` folder contains the dataset in parquet format, where `train` prefix indicates it corresponds to the images and metadata in `train.csv`, while `validation` corresponds to `val.csv`. These are rendered by the dataset viewer.
+The `data/` folder contains the dataset in parquet format, where `train` prefix indicates it corresponds to the images and metadata in `train.csv`, while `validation` corresponds to `val.csv`. Similarly:
+
+`seen` -> `seen_domain.csv`
+`unseen` -> `unseen_domain.csv`
+`seen_challenge` -> `seen_domain_challenge.csv`
+`unseen_challenge` -> `unseen_domain_challenge.csv`
+
+These are rendered by the dataset viewer.
 
 ### Data Fields
 
-Both `train.csv` and `val.csv` have the following columns.
+`train.csv`, `val.csv`, `seen_domain.csv`, `seen_domain_challenge.csv`, `unseen_domain.csv`, `unseen_domain_challenge.csv` have the following columns.
 | fieldName | description | dataType | relatedTerms |
 |---|---|---|---|
 | eventID | An (anonymized) identifier for the set of information associated with the event, which includes information about the place and time of the event | string | [DWC_v2009-04-24:eventID](http://rs.tdwg.org/dwc/terms/history/index.htm#eventID-2009-04-24)